1. Field of the Invention
The present invention generally relates to image processing, and specifically, a method and an apparatus for tracking an object in the computer vision technology.
2. Description of the Related Art
Currently, the human-computer interaction system is getting a lot of attention, because the operation mode is very easy and convenient for the user. In particular, the hand gesture control system is very convenient for the user. An effective hand gesture recognition system can provide a natural and effective interaction method. In the hand gesture recognition system, the hand tracking is a very important part.
In order to be operated by a user, in a hand tracking system, it is required for the user not to wear any special equipment, such as a special glove, a color marker, etc. Furthermore, the hand is a non-rigid object and has the characteristics of fast movement, easy distortion and self-shielding, therefore the hand tracking technology is a very challenging task.
The U.S. Patent Publication US20100310127A1 discloses an object tracking method. In this patent, there are two different templates for tracking, namely, an initial template and a dynamic template. A tracking result is determined by one or two of an initial template tracking result and a dynamic template tracking result. Meanwhile, a decision-making unit determines whether to update the dynamic template or not. The dynamic template is updated by the initial template and a target image. In this patent, the initial template is never updated, and the dynamic template is updated by the initial template and the target image. Thus, the initial template may be inapplicable to a current environment when the tracking environment changes frequently, therefore such a tracking method is not robust.
In the article published in February 2008 on Image Processing, IEEE Transactions, Volume 17, Issue 2, for which the authors are Junqiu Wang et al., and the title is “Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking”, a new target template update method based on an adaptive selection of features is provided. In such a tracking method, the best two features are combined by using a joint histogram. In the article, the feature selection is performed for every 8 to 12 frames. The target template is updated by calculating a similarity between a current template and an initial template. In the article, an alternative update method by considering a relationship among the initial template, a previous template and a current candidate image is provided. In the article, the initial template is a fixed template, is formed by tracking an artificially defined before the start-up or detected object, and never changes during the whole process.